Researchers at the University of Pompeu Fabra, Cardiff University and the Technical University of Madrid used machine-learning algorithms to discover new things about the history of music. One of the main tasks of musicology researchers is to develop and validate musical hypotheses, after studying historical documents and other available information. Many historical documents have now been digitized and can be accessed and browsed on a computer, making it easy for researchers to access them online. However, basic search engines operate at an "exact text string matching" level, and hence do not always capture the underlying meaning in the content. In a recently published study, music data science researcher Sergio Oramas and his colleagues tested natural language processing (NLP) approaches that could make the most out of archived historical documents, helping scientists to uncover new hypotheses and identifying interesting patterns in available data.

Twitter recently took drastic action as part of an effort to slow the spread of misinformation through its platform, shutting down more than two million automated accounts, or bots. You can expect the tricksters to up their game when it comes to disguising fake users as real ones. It's important not to be swayed by fake accounts or waste your time arguing with them, and identifying bots in a Twitter thread has become a strange version of the Turing test. Accusing posters of being bots has even become an oddly satisfying way to insult their intelligence. Advances in machine learning hint at how bots could become more humanlike.

One of the most surprising biographical tidbits in McQueen, the new documentary about the late fashion designer Alexander McQueen, is that he didn't know a collection could tell a "story" until he was several apprenticeships into the fashion industry. He was obviously a fast learner. Even among top-tier designers, McQueen became well-known for his theatrical runway shows. The half-dozen or so presentations we see in the film evoke Jack the Ripper, a mental asylum, sexual assault, robots, demons, goddesses, and animal chimeras. Not all the shows were well received. Directors Ian Bonhôte and Peter Ettedgui's smartest tactic--the one that makes McQueen such a pleasure to watch, even for fashion outsiders--is giving viewers a front-row seat to the runway, then letting us judge the designer's oeuvre for ourselves.

Last year, Elon Musk made headlines by describing AI as a "fundamental risk to the existence of civilization." At the time, Facebook CEO Mark Zuckerburg described such warnings as "pretty irresponsible." More recently, Google CEO Eric Schmidt suggested that the answer to fears about AI was to police it: "The example I would offer is, would you not invent the telephone because of the possible misuse of the telephone by evil people? No, you would build the telephone and you would try to find a way to police the misuse of the telephone," he said at the VivaTech conference in Paris last month. Others talk about the singularity – the point at which an AI suddenly becomes sentient – and use that possibility to stoke fears already fueled by dozens of sci-fi movies.

While machine intelligence is certain to play a key role in the creation of next generation systems in a wide variety of industry sectors in the near future, it is particularly relevant in rapidly developing industries such as ICT, manufacturing and transportation. Across the globe, mobile operators are getting ready to deploy the 5th generation of 3GPP mobile wireless networks (5G). Compared to the mobile infrastructure that is currently in place, 5G will bring higher throughput, lower latency, more efficient signaling, support for more spectrum bands, more programmability and other additional advanced techniques to maximize usage and optimize costs [1]. The number of connected devices will greatly increase as a result of this improved performance: sensors will benefit from more affordable bandwidth to the internet; heavy users of uplink traffic like video cameras will be able to share more data; fast-moving devices (drones, cars) will have more reliable connectivity and so on. These new devices will be the catalysts of a new wave of innovation for all involved industries.

Machine learning is the idea that describes computers that can essentially "learn" and process new information without specifically being programed to do so. If you give a computer a task, it will more-or-less get better at that task the more it has a chance to engage in it. Object detection is a subset of this idea and is of particular relevance to photos. Not only does object detection let you know which objects are in a photo (hence the name), it also gives you insight into precisely where they are, too. But out of all the industries and activities where object detection is poised to make a big impact, drone services are undoubtedly right at the top.

This is the second story in our continuing series covering the basics of artificial intelligence. While it isn't necessary to read the first article, which …